{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "cd88e3fd",
   "metadata": {},
   "source": [
    "1、导入所需要的包"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "c686f5bd",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from datetime import datetime\n",
    "from sklearn.preprocessing import MinMaxScaler\n",
    "from sklearn.metrics import mean_squared_error, r2_score\n",
    "from tensorflow.keras.models import Sequential\n",
    "from tensorflow.keras.layers import LSTM, Dense, Dropout\n",
    "import baostock as bs\n",
    "\n",
    "# 全局配置：解决中文显示、设置图表风格\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']\n",
    "plt.rcParams['axes.unicode_minus'] = False\n",
    "plt.style.use('seaborn-v0_8-whitegrid')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ee4e96b9",
   "metadata": {},
   "source": [
    "2、从Baostock获取指定股票的月度数据"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cb80d9e3",
   "metadata": {},
   "source": [
    "3、数据预处理：字段类型转换+命名对齐"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "01002405",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_data(code):\n",
    "    # 时间范围：近8年（足够LSTM训练）\n",
    "    end = datetime.now()\n",
    "    start = datetime(end.year - 8, end.month, end.day)  # 取近8年数据\n",
    "    start_str = start.strftime('%Y-%m-%d')\n",
    "    end_str = end.strftime('%Y-%m-%d')\n",
    "\n",
    "    # 登录Baostock\n",
    "    lg = bs.login()\n",
    "    if lg.error_code != '0':\n",
    "        print(f\"Baostock登录失败：{lg.error_msg}\")\n",
    "        return None\n",
    "\n",
    "    # 获取月度数据（frequency='m'）\n",
    "    rs_result = bs.query_history_k_data_plus(\n",
    "        code=code,\n",
    "        fields=\"date,close,volume\",  # 取日期、收盘价、成交量\n",
    "        start_date=start_str,\n",
    "        end_date=end_str,\n",
    "        frequency=\"m\",  # 月度数据\n",
    "        adjustflag=\"2\"  # 后复权（适配真实收益计算）\n",
    "    )\n",
    "\n",
    "    df_result = rs_result.get_data()\n",
    "    bs.logout()  # 登出\n",
    "\n",
    "    \n",
    "    #数据预处理\n",
    "    df_result['date'] = pd.to_datetime(df_result['date'])\n",
    "    df_result['close_price'] = pd.to_numeric(df_result['close'], errors='coerce')\n",
    "    df_result['volume'] = pd.to_numeric(df_result['volume'], errors='coerce')\n",
    "    df_result = df_result[['date', 'close_price', 'volume']].set_index('date').sort_index()\n",
    "    df_result.dropna(inplace=True)  # 清洗空值\n",
    "    print(f\"成功获取宁德时代月度数据：{len(df_result)}条记录，时间范围：{df_result.index[0].strftime('%Y-%m')} 至 {df_result.index[-1].strftime('%Y-%m')}\")\n",
    "    return df_result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "3ecd29d6",
   "metadata": {},
   "outputs": [],
   "source": [
    "def preprocess_and_describe(df):\n",
    "    df_processed = df.copy()\n",
    "    # 计算月度收益率（预测目标）\n",
    "    df_processed[\"monthly_return\"] = df_processed[\"close_price\"].pct_change() * 100\n",
    "    # 成交量月度增长率（辅助特征）\n",
    "    df_processed[\"volume_growth\"] = df_processed[\"volume\"].pct_change() * 100\n",
    "    # 滞后收益率特征（前1-3个月）\n",
    "    for lag in range(1, 4):\n",
    "        df_processed[f\"lag_{lag}_return\"] = df_processed[\"monthly_return\"].shift(lag)\n",
    "\n",
    "    df_processed.dropna(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "70a3f3d7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "login success!\n",
      "logout success!\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\xiya\\AppData\\Local\\Temp\\ipykernel_11556\\3678350201.py:25: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead.\n",
      "  df_monthly = df.resample('M', on='date').last().dropna()\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import baostock as bs\n",
    "from datetime import datetime\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']\n",
    "plt.rcParams['axes.unicode_minus'] = False\n",
    "#获取宁德时代数据并预处理\n",
    "def get_ningde_data():\n",
    "    \"\"\"获取宁德时代月度收盘价，计算月度收益率\"\"\"\n",
    "    bs.login()\n",
    "    \n",
    "    # 获取近3年日线数据\n",
    "    end_date = datetime.now().strftime(\"%Y-%m-%d\")\n",
    "    start_date = (datetime.now().replace(year=datetime.now().year-3)).strftime(\"%Y-%m-%d\")\n",
    "    \n",
    "    rs = bs.query_history_k_data_plus(\n",
    "        \"sz.300750\", \"date,close\",\n",
    "        start_date=start_date, end_date=end_date, frequency=\"d\"\n",
    "    )\n",
    "    df = rs.get_data()\n",
    "    df['date'] = pd.to_datetime(df['date'])\n",
    "    df['close'] = pd.to_numeric(df['close'])\n",
    "    \n",
    "    # 按月重采样，取每月最后一个交易日的收盘价\n",
    "    df_monthly = df.resample('M', on='date').last().dropna()\n",
    "    df_monthly.columns = ['close_price']\n",
    "    \n",
    "    # 计算月度收益率（(本月收盘价-上月收盘价)/上月收盘价 *100）\n",
    "    df_monthly['monthly_return'] = df_monthly['close_price'].pct_change() * 100\n",
    "    df_monthly = df_monthly.dropna()  # 删除第一行（无上月数据）\n",
    "    \n",
    "    bs.logout()\n",
    "    return df_monthly\n",
    "# 获取预处理后的数据\n",
    "df_processed = get_ningde_data()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0b3bd39e",
   "metadata": {},
   "source": [
    "4、描述性统计"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "a06438fb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "宁德时代月度收益率描述性统计\n",
      "==================================================\n",
      "count    36.00\n",
      "mean      0.80\n",
      "std      13.25\n",
      "min     -43.15\n",
      "25%      -4.40\n",
      "50%       0.01\n",
      "75%       5.24\n",
      "max      36.64\n",
      "偏度       -0.10\n",
      "峰度        3.98\n",
      "Name: monthly_return, dtype: float64\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 描述性统计\n",
    "def preprocess_and_describe(df):\n",
    "    print(\"宁德时代月度收益率描述性统计\")\n",
    "    print(\"=\"*50)\n",
    "    return_stats = df[\"monthly_return\"].describe()\n",
    "    return_stats[\"偏度\"] = df[\"monthly_return\"].skew()\n",
    "    return_stats[\"峰度\"] = df[\"monthly_return\"].kurt()\n",
    "    print(return_stats.round(2))\n",
    "    # 执行统计\n",
    "preprocess_and_describe(df_processed)\n",
    "fig, axes = plt.subplots(2, 2, figsize=(12, 6))\n",
    "\n",
    "# 子图1：月度收盘价趋势\n",
    "axes[0, 0].plot(df_processed.index, df_processed[\"close_price\"], color=\"#1f77b4\")\n",
    "axes[0, 0].set_title(\"宁德时代月度收盘价趋势\", fontsize=12)\n",
    "axes[0, 0].set_ylabel(\"收盘价（元）\")\n",
    "axes[0, 0].tick_params(axis=\"x\", rotation=45)\n",
    "\n",
    "# 子图2：月度收益率趋势\n",
    "axes[0, 1].plot(df_processed.index, df_processed[\"monthly_return\"], color=\"#ff7f0e\")\n",
    "axes[0, 1].axhline(y=0, color=\"black\", linestyle=\"--\", alpha=0.5)\n",
    "axes[0, 1].set_title(\"宁德时代月度收益率趋势\", fontsize=12)\n",
    "axes[0, 1].set_ylabel(\"收益率（%）\")\n",
    "axes[0, 1].tick_params(axis=\"x\", rotation=45)\n",
    "# 子图3：收益率直方图\n",
    "axes[1, 0].hist(df_processed[\"monthly_return\"], bins=15, color=\"#2ca02c\", alpha=0.7)\n",
    "axes[1, 0].set_title(\"月度收益率分布\", fontsize=12)\n",
    "axes[1, 0].set_xlabel(\"收益率（%）\")\n",
    "axes[1, 0].set_ylabel(\"频数\")\n",
    "\n",
    "# 子图4：收盘价与收益率散点图\n",
    "axes[1, 1].scatter(df_processed[\"close_price\"], df_processed[\"monthly_return\"], color=\"#d62728\", alpha=0.6)\n",
    "axes[1, 1].set_title(\"收盘价 vs 收益率\", fontsize=12)\n",
    "axes[1, 1].set_xlabel(\"收盘价（元）\")\n",
    "axes[1, 1].set_ylabel(\"收益率（%）\")\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "71027226",
   "metadata": {},
   "source": [
    "5、LSTM模型构建与验证，未来收益预测"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "1c593924",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.preprocessing import MinMaxScaler\n",
    "from tensorflow.keras.models import Sequential\n",
    "from tensorflow.keras.layers import LSTM, Dense, Dropout\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']\n",
    "plt.rcParams['axes.unicode_minus'] = False\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "d8739379",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "# 步骤1：构建多特征数据集 \n",
    "def build_feature_dataset(n=200):\n",
    "    \"\"\"生成带滞后收益、成交量增长的模拟数据集\"\"\"\n",
    "    np.random.seed(42)\n",
    "    df = pd.DataFrame({\n",
    "        \"monthly_return\": np.random.randn(n) * 5 + 2,\n",
    "        \"volume_growth\": np.random.randn(n) * 3 + 10\n",
    "    })\n",
    "    # 添加滞后收益特征\n",
    "    for lag in [1, 2, 3]:\n",
    "        df[f\"lag_{lag}_return\"] = df[\"monthly_return\"].shift(lag)\n",
    "    return df.dropna()\n",
    "\n",
    "df_processed = build_feature_dataset()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "7755e192",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "✅ LSTM模型结构：\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "d:\\anaconda\\Lib\\site-packages\\keras\\src\\layers\\rnn\\rnn.py:199: UserWarning: Do not pass an `input_shape`/`input_dim` argument to a layer. When using Sequential models, prefer using an `Input(shape)` object as the first layer in the model instead.\n",
      "  super().__init__(**kwargs)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Model: \"Mingo_LSTM_Return_Predictor\"</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1mModel: \"Mingo_LSTM_Return_Predictor\"\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃<span style=\"font-weight: bold\"> Layer (type)                    </span>┃<span style=\"font-weight: bold\"> Output Shape           </span>┃<span style=\"font-weight: bold\">       Param # </span>┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ LSTM_1 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">LSTM</span>)                   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">6</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">59</span>)          │        <span style=\"color: #00af00; text-decoration-color: #00af00\">15,104</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Dropout_1 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dropout</span>)             │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">6</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">59</span>)          │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ LSTM_2 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">LSTM</span>)                   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">59</span>)             │        <span style=\"color: #00af00; text-decoration-color: #00af00\">28,084</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Dropout_2 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dropout</span>)             │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">59</span>)             │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Dense_1 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                 │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">25</span>)             │         <span style=\"color: #00af00; text-decoration-color: #00af00\">1,500</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Output_Layer (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)            │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">1</span>)              │            <span style=\"color: #00af00; text-decoration-color: #00af00\">26</span> │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
       "</pre>\n"
      ],
      "text/plain": [
       "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃\u001b[1m \u001b[0m\u001b[1mLayer (type)                   \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape          \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m      Param #\u001b[0m\u001b[1m \u001b[0m┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ LSTM_1 (\u001b[38;5;33mLSTM\u001b[0m)                   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m6\u001b[0m, \u001b[38;5;34m59\u001b[0m)          │        \u001b[38;5;34m15,104\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Dropout_1 (\u001b[38;5;33mDropout\u001b[0m)             │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m6\u001b[0m, \u001b[38;5;34m59\u001b[0m)          │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ LSTM_2 (\u001b[38;5;33mLSTM\u001b[0m)                   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m59\u001b[0m)             │        \u001b[38;5;34m28,084\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Dropout_2 (\u001b[38;5;33mDropout\u001b[0m)             │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m59\u001b[0m)             │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Dense_1 (\u001b[38;5;33mDense\u001b[0m)                 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m25\u001b[0m)             │         \u001b[38;5;34m1,500\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ Output_Layer (\u001b[38;5;33mDense\u001b[0m)            │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m)              │            \u001b[38;5;34m26\u001b[0m │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Total params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">44,714</span> (174.66 KB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Total params: \u001b[0m\u001b[38;5;34m44,714\u001b[0m (174.66 KB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">44,714</span> (174.66 KB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m44,714\u001b[0m (174.66 KB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Non-trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> (0.00 B)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "🔄 开始训练LSTM模型...\n",
      "Epoch 1/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 80ms/step - loss: 0.1129 - val_loss: 0.0498\n",
      "Epoch 2/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 14ms/step - loss: 0.0432 - val_loss: 0.0385\n",
      "Epoch 3/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 13ms/step - loss: 0.0370 - val_loss: 0.0295\n",
      "Epoch 4/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 13ms/step - loss: 0.0338 - val_loss: 0.0292\n",
      "Epoch 5/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 12ms/step - loss: 0.0335 - val_loss: 0.0303\n",
      "Epoch 6/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 13ms/step - loss: 0.0342 - val_loss: 0.0297\n",
      "Epoch 7/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 11ms/step - loss: 0.0342 - val_loss: 0.0300\n",
      "Epoch 8/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 13ms/step - loss: 0.0351 - val_loss: 0.0317\n",
      "Epoch 9/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 16ms/step - loss: 0.0340 - val_loss: 0.0295\n",
      "Epoch 10/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 14ms/step - loss: 0.0325 - val_loss: 0.0306\n",
      "Epoch 11/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 12ms/step - loss: 0.0330 - val_loss: 0.0298\n",
      "Epoch 12/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 13ms/step - loss: 0.0337 - val_loss: 0.0293\n",
      "Epoch 13/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 14ms/step - loss: 0.0348 - val_loss: 0.0311\n",
      "Epoch 14/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 15ms/step - loss: 0.0335 - val_loss: 0.0295\n",
      "Epoch 15/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 16ms/step - loss: 0.0340 - val_loss: 0.0305\n",
      "Epoch 16/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 12ms/step - loss: 0.0319 - val_loss: 0.0299\n",
      "Epoch 17/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 14ms/step - loss: 0.0309 - val_loss: 0.0302\n",
      "Epoch 18/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 12ms/step - loss: 0.0324 - val_loss: 0.0307\n",
      "Epoch 19/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 13ms/step - loss: 0.0332 - val_loss: 0.0296\n",
      "Epoch 20/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 12ms/step - loss: 0.0326 - val_loss: 0.0308\n",
      "Epoch 21/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 13ms/step - loss: 0.0318 - val_loss: 0.0298\n",
      "Epoch 22/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 17ms/step - loss: 0.0337 - val_loss: 0.0304\n",
      "Epoch 23/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 14ms/step - loss: 0.0318 - val_loss: 0.0307\n",
      "Epoch 24/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 13ms/step - loss: 0.0326 - val_loss: 0.0294\n",
      "Epoch 25/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 12ms/step - loss: 0.0322 - val_loss: 0.0303\n",
      "Epoch 26/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 12ms/step - loss: 0.0327 - val_loss: 0.0306\n",
      "Epoch 27/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 14ms/step - loss: 0.0335 - val_loss: 0.0298\n",
      "Epoch 28/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 13ms/step - loss: 0.0314 - val_loss: 0.0310\n",
      "Epoch 29/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - loss: 0.0350 - val_loss: 0.0300\n",
      "Epoch 30/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 12ms/step - loss: 0.0313 - val_loss: 0.0309\n",
      "Epoch 31/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 12ms/step - loss: 0.0306 - val_loss: 0.0294\n",
      "Epoch 32/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 12ms/step - loss: 0.0318 - val_loss: 0.0302\n",
      "Epoch 33/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 12ms/step - loss: 0.0309 - val_loss: 0.0293\n",
      "Epoch 34/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 12ms/step - loss: 0.0321 - val_loss: 0.0303\n",
      "Epoch 35/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 12ms/step - loss: 0.0316 - val_loss: 0.0304\n",
      "Epoch 36/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 13ms/step - loss: 0.0326 - val_loss: 0.0296\n",
      "Epoch 37/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 13ms/step - loss: 0.0327 - val_loss: 0.0305\n",
      "Epoch 38/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 14ms/step - loss: 0.0303 - val_loss: 0.0304\n",
      "Epoch 39/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 12ms/step - loss: 0.0322 - val_loss: 0.0301\n",
      "Epoch 40/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 13ms/step - loss: 0.0303 - val_loss: 0.0306\n",
      "Epoch 41/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 13ms/step - loss: 0.0317 - val_loss: 0.0309\n",
      "Epoch 42/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 13ms/step - loss: 0.0305 - val_loss: 0.0295\n",
      "Epoch 43/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 12ms/step - loss: 0.0313 - val_loss: 0.0301\n",
      "Epoch 44/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 14ms/step - loss: 0.0316 - val_loss: 0.0319\n",
      "Epoch 45/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 13ms/step - loss: 0.0311 - val_loss: 0.0302\n",
      "Epoch 46/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 14ms/step - loss: 0.0314 - val_loss: 0.0316\n",
      "Epoch 47/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 12ms/step - loss: 0.0330 - val_loss: 0.0319\n",
      "Epoch 48/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 12ms/step - loss: 0.0340 - val_loss: 0.0306\n",
      "Epoch 49/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 13ms/step - loss: 0.0320 - val_loss: 0.0316\n",
      "Epoch 50/50\n",
      "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 13ms/step - loss: 0.0300 - val_loss: 0.0296\n"
     ]
    }
   ],
   "source": [
    "# 步骤2：训练多特征LSTM模型 \n",
    "def build_and_train_lstm(df, time_steps=6):\n",
    "    # 定义特征和目标\n",
    "    features = [\"lag_1_return\", \"lag_2_return\", \"lag_3_return\", \"volume_growth\"]\n",
    "    target = \"monthly_return\"\n",
    "    \n",
    "    # 归一化\n",
    "    scaler_X = MinMaxScaler(feature_range=(0, 1))\n",
    "    scaler_Y = MinMaxScaler(feature_range=(0, 1))\n",
    "    X_scaled = scaler_X.fit_transform(df[features].values)\n",
    "    Y_scaled = scaler_Y.fit_transform(df[target].values.reshape(-1, 1))\n",
    "    \n",
    "    # 生成LSTM输入序列\n",
    "    X_lstm, Y_lstm = [], []\n",
    "    for i in range(time_steps, len(X_scaled)):\n",
    "        X_lstm.append(X_scaled[i-time_steps:i, :])\n",
    "        Y_lstm.append(Y_scaled[i, 0])\n",
    "    X_lstm, Y_lstm = np.array(X_lstm), np.array(Y_lstm)\n",
    "    \n",
    "    # 划分训练/测试集\n",
    "    train_size = int(0.8 * len(X_lstm))\n",
    "    X_train, X_test = X_lstm[:train_size], X_lstm[train_size:]\n",
    "    Y_train, Y_test = Y_lstm[:train_size], Y_lstm[train_size:]\n",
    "    \n",
    "    # 构建模型\n",
    "    model = Sequential(name=\"Mingo_LSTM_Return_Predictor\")\n",
    "    model.add(LSTM(units=59, return_sequences=True, input_shape=(X_train.shape[1], X_train.shape[2]), name=\"LSTM_1\"))\n",
    "    model.add(Dropout(0.2, name=\"Dropout_1\"))\n",
    "    model.add(LSTM(units=59, return_sequences=False, name=\"LSTM_2\"))\n",
    "    model.add(Dropout(0.2, name=\"Dropout_2\"))\n",
    "    model.add(Dense(units=25, name=\"Dense_1\"))\n",
    "    model.add(Dense(units=1, name=\"Output_Layer\"))\n",
    "    \n",
    "    model.compile(optimizer=\"adam\", loss=\"mean_squared_error\")\n",
    "    print(\"\\n✅ LSTM模型结构：\")\n",
    "    model.summary()\n",
    "    \n",
    "    # 训练模型\n",
    "    print(\"\\n🔄 开始训练LSTM模型...\")\n",
    "    history = model.fit(\n",
    "        X_train, Y_train,\n",
    "        batch_size=16,\n",
    "        epochs=50,\n",
    "        validation_data=(X_test, Y_test),\n",
    "        verbose=1\n",
    "    )\n",
    "    \n",
    "    return model, history, X_train, X_test, Y_train, Y_test, scaler_X, scaler_Y, time_steps\n",
    "\n",
    "model, history, X_train, X_test, Y_train, Y_test, scaler_X, scaler_Y, time_steps = build_and_train_lstm(df_processed)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "6bfeee4c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "📊 测试集验证结果：\n",
      "均方误差（MSE）：21.1362\n",
      "均方根误差（RMSE）：4.5974\n",
      "决定系数（R²）：-0.0518\n"
     ]
    }
   ],
   "source": [
    "#  步骤3：模型验证与误差评估 \n",
    "def validate_model(model, X_test, Y_test, scaler_Y):\n",
    "    # 测试集预测\n",
    "    Y_test_pred_scaled = model.predict(X_test, verbose=0)\n",
    "    Y_test_pred = scaler_Y.inverse_transform(Y_test_pred_scaled)\n",
    "    Y_test_true = scaler_Y.inverse_transform(Y_test.reshape(-1, 1))\n",
    "    \n",
    "    # 计算误差\n",
    "    mse = np.mean((Y_test_pred - Y_test_true) ** 2)\n",
    "    rmse = np.sqrt(mse)\n",
    "    r2 = 1 - (np.sum((Y_test_true - Y_test_pred) ** 2) / np.sum((Y_test_true - np.mean(Y_test_true)) ** 2))\n",
    "    \n",
    "    print(\"\\n📊 测试集验证结果：\")\n",
    "    print(f\"均方误差（MSE）：{mse:.4f}\")\n",
    "    print(f\"均方根误差（RMSE）：{rmse:.4f}\")\n",
    "    print(f\"决定系数（R²）：{r2:.4f}\")\n",
    "    return Y_test_pred, Y_test_true\n",
    "\n",
    "Y_test_pred, Y_test_true = validate_model(model, X_test, Y_test, scaler_Y)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "68775794",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#  步骤4：损失曲线与预测结果可视化 \n",
    "def plot_results(history, Y_train, Y_test_true, Y_test_pred, scaler_Y):\n",
    "    # 损失曲线\n",
    "    plt.figure(figsize=(12, 4))\n",
    "    plt.plot(history.history[\"loss\"], label=\"训练损失\", color=\"#1f77b4\")\n",
    "    plt.plot(history.history[\"val_loss\"], label=\"验证损失\", color=\"#ff7f0e\")\n",
    "    plt.title(\"LSTM模型损失变化\", fontsize=12)\n",
    "    plt.xlabel(\"epoch\")\n",
    "    plt.ylabel(\"均方误差\")\n",
    "    plt.legend()\n",
    "    plt.grid(alpha=0.3)\n",
    "    plt.show()\n",
    "    \n",
    "    # 预测结果\n",
    "    Y_train_true = scaler_Y.inverse_transform(Y_train.reshape(-1, 1))\n",
    "    Y_train_pred = scaler_Y.inverse_transform(model.predict(X_train, verbose=0))\n",
    "    \n",
    "    plt.figure(figsize=(14, 6))\n",
    "    plt.plot(np.concatenate([Y_train_true, Y_test_true]), label=\"真实收益率\", color=\"#2ca02c\", alpha=0.7)\n",
    "    plt.plot(np.concatenate([Y_train_pred, Y_test_pred]), label=\"模型预测收益率\", color=\"#d62728\", linestyle=\"--\")\n",
    "    plt.title(\"多特征LSTM收益率预测结果\", fontsize=14)\n",
    "    plt.xlabel(\"时间步\")\n",
    "    plt.ylabel(\"收益率（%）\")\n",
    "    plt.legend()\n",
    "    plt.grid(alpha=0.3)\n",
    "    plt.tight_layout()\n",
    "    plt.show()\n",
    "\n",
    "plot_results(history, Y_train, Y_test_true, Y_test_pred, scaler_Y)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "1f1582ea",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "🔮 未来12步预测收益率：\n",
      "[[1.65]\n",
      " [1.87]\n",
      " [1.7 ]\n",
      " [1.34]\n",
      " [1.48]\n",
      " [1.31]\n",
      " [1.3 ]\n",
      " [1.28]\n",
      " [1.25]\n",
      " [1.23]\n",
      " [1.22]\n",
      " [1.2 ]]\n"
     ]
    }
   ],
   "source": [
    "# 步骤5：未来收益预测 \n",
    "def predict_future_returns(model, df, scaler_X, scaler_Y, time_steps, forecast_period=12):\n",
    "    # 获取最后一段特征序列\n",
    "    last_features = df[[\"lag_1_return\", \"lag_2_return\", \"lag_3_return\", \"volume_growth\"]].values[-time_steps:]\n",
    "    last_features_scaled = scaler_X.transform(last_features)\n",
    "    \n",
    "    # 滚动预测未来\n",
    "    future_preds_scaled = []\n",
    "    current_seq = last_features_scaled.copy()\n",
    "    for _ in range(forecast_period):\n",
    "        pred = model.predict(current_seq.reshape(1, time_steps, 4), verbose=0)\n",
    "        future_preds_scaled.append(pred[0, 0])\n",
    "        \n",
    "        # 更新序列（滞后特征逻辑）\n",
    "        new_lag1 = pred[0, 0]\n",
    "        new_lag2 = current_seq[-1, 0]\n",
    "        new_lag3 = current_seq[-1, 1]\n",
    "        new_volume = current_seq[-1, 3]  # 假设成交量增长延续\n",
    "        current_seq = np.roll(current_seq, -1, axis=0)\n",
    "        current_seq[-1] = [new_lag1, new_lag2, new_lag3, new_volume]\n",
    "    \n",
    "    # 逆标准化\n",
    "    future_preds = scaler_Y.inverse_transform(np.array(future_preds_scaled).reshape(-1, 1))\n",
    "    return future_preds\n",
    "\n",
    "future_returns = predict_future_returns(model, df_processed, scaler_X, scaler_Y, time_steps)\n",
    "print(\"\\n🔮 未来12步预测收益率：\")\n",
    "print(future_returns.round(2))"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "base",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.13.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
